Tag: product-market fit lessons

Scaling 16 ‘Startups Within a Startup’: My Enterprise GTM, PMF, and Sales Hiring Playbook

I’ve long believed the most resilient software companies master two hard things at once: they move decisively from mid-market to enterprise, and they ship multiple “best-of-breed” products without losing focus. The operating model that makes this possible — running 16 “startups within a startup” — resonates with how I build product organizations. In this piece, I’m unpacking the frameworks I use to make that model work at scale, from “product-market-sales fit” to capacity-driven go-to-market.

Why do companies get stuck in the mid-market? In my experience, it’s rarely just sales execution. It’s usually a product readiness gap hiding inside a distribution story. Enterprise customers expect battle-tested architecture, deep security and compliance, robust RBAC, data governance, audit trails, and predictable SLAs. They also expect a clear value proposition, strong references, and a crisp “who do we beat and why” articulation. If any one of those is fuzzy, your deals elongate or disappear. The fix starts by designing intentionally for enterprise and mid-market from day one: plan for scale, extensibility, change management, and procurement complexity — then validate with lighthouse customers, not just friendly pilots.

Sometimes the hardest enterprise move is saying no. I’ve advised teams to walk away from a marquee logo like Netflix when the requirements force unnatural acts that derail your roadmap. It feels counterintuitive — especially when the logo is irresistible — but your ideal customer profile must govern priorities. Your long-term velocity compounds when you align deeply with the customers who value your native strengths.

I differentiate between “product-market-fit” and “product-market-sales fit.” The former tells me a product delivers undeniable value; the latter tells me my distribution system can reproduce that value at scale. I watch for signals beyond anecdotes: win rates by segment, cycle time, ramp time to first deal, multi-threading depth, net revenue retention, and the percentage of customers who expand within two quarters. When these lag, I diagnose whether I have a product problem (insufficient value or clear “must-have” outcomes) or a distribution problem (positioning, enablement, or segmentation). The diagnosis determines whether I ship features, sharpen messaging, or rewire the motion.

On go-to-market, I build a capacity-driven machine instead of chasing deals. That means matching pipeline health to quota capacity, calibrating territories to intent density, and instrumenting enablement so new reps reach productivity with consistent talk tracks and crisp objection handling. I prefer simple, repeatable plays that compound: a precise ICP, strong proof packages, and a pricing model that meets customers where they are. When those are humming, founder-led GTM transitions smoothly to a scalable sales engine without losing the product’s original edge.

Hiring your first head of sales is a leverage point. I look for four things: pattern recognition in my specific segment, a builder’s mindset (process and playbooks without bureaucracy), rigorous pipeline hygiene, and the ability to partner with product on “where we win and why.” In the interview, I run scenario loops: how they’d disqualify non-ICP deals, how they’d recover a late-stage stall, how they’d deliver the first 90 days plan, and how they’d coach to a consistent message. Early founders absolutely need to learn sales — not to become the forever closer, but to encode customer truth into the product and the motion.

Strategic timing matters, too. There’s a well-known case of selling three days pre-IPO; whether or not you’d make the same call, the lesson stands: market timing, certainty of outcome, and board alignment are strategic variables, not afterthoughts. A healthy board brings independent thinking, timely guidance on capital and risk, and a unified narrative — especially when the market is volatile.

On competition, I pressure-test our narrative around points of parity and a “binary differentiator.” In crowded markets, incremental advantages don’t move the needle. You need one thing customers can’t ignore — faster time-to-value, a step-function in accuracy, or a cost curve that resets the category. I ask every team to prove a binary outcome: if we’re in the eval, there’s a clear, testable reason we win.

Launching multiple products simultaneously demands ruthless clarity. I structure the org as “startups within a startup,” each with its own GM, product roadmap, and GTM targets, but anchored to a shared platform for identity, data, and extensibility. Product managers operate as mini-entrepreneurs — owning P&L-like metrics, customer outcomes, and crisp product positioning — while a central platform team ensures consistency and speed. The rallying cry across these teams is simple: “We need to be best of breed.” If a product can’t credibly win on its merits, we either sharpen it until it does or we stop investing.

Execution lives in the details. I emphasize outcomes vs output OKRs, product trios for tight alignment, and continuous improvement powered by CI/CD so we can learn faster. We track DORA metrics like deployment frequency to ensure our cadence supports enterprise reliability. Weekly operating reviews focus on value delivered: have we solved the customer’s core job, and can our sales and success teams prove it with repeatable stories? When the answer is yes, expansion follows naturally.

Bringing it all together: moving upmarket, building “product-market-sales fit,” and running 16 product lines under one roof is achievable with the right structure and discipline. Design for enterprise from the start, let your ICP guide every trade-off, anchor GTM in capacity and repeatability, hire sales leaders who build with you, enforce a “binary differentiator,” and empower product managers as owners. Do that, and the “startups within a startup” model becomes a force multiplier — not just a slogan.

November 19, 2025
The Product Positioning Statement Playbook: Build a Message That Wins and Endures

Your product positioning statement decides if you stand the test of time. I’ve seen this truth play out across launches, pivots, and category-defining moments—when the positioning is razor sharp, everything from roadmap to revenue snaps into alignment. When it’s vague, teams ship features, but customers don’t buy the story.

At HighLevel, I’ve led product trios and go-to-market teams through the hard work of distilling complex value into a single, credible promise. The pattern is consistent: the best positioning clarifies who we serve, the problem we own, the market category we play in, and the competitive differentiation that earns us the right to win.

Positioning is not a tagline or a homepage headline; it’s the narrative spine that informs value proposition, messaging, pricing, user activation, sales enablement, and product-led growth. It’s also how we drive internal focus—shaping outcomes vs output OKRs, roadmap trade-offs, and investment bets with discipline.

Here’s the anatomy I rely on: target customer and context; problem worth solving; category anchor (what buyers already recognize); value proposition (the outcome we deliver); points of parity (table stakes we meet) and points of differentiation (where we win); and proof—evidence that reduces risk for the buyer. When each element is explicit, your product positioning becomes both compelling and testable.

Use a simple scaffold to draft quickly: For [target customer], who [urgent need or job-to-be-done], [product] is a [recognized category] that [core value proposition]. Unlike [primary alternatives], it [distinct, defensible differentiation]—proven by [evidence: results, usage, social proof, or integrations]. Write it plainly enough that a sales rep can say it and a customer can repeat it.

Then pressure-test. In product discovery, validate the language with real customers—do they self-identify as the target and echo the outcome? In analytics, check if activation and retention analysis improve when onboarding, in-app guides, and product tours mirror the positioning. In go-to-market strategy, A/B test messaging in campaigns and sales conversations, and listen for shorter time-to-understanding and cleaner objection handling.

Expert products operationalize positioning across the journey. The category and value proposition show up consistently on the pricing page, inside onboarding tooltips, in CRM integration notes, and within sales collateral. Product management leadership, marketing, and sales align weekly on one narrative, and product-led growth metrics verify that narrative with behavior, not just opinions.

To write one that sticks, I take this sequence: define the narrowest viable target; articulate the must-solve problem in the customer’s words; choose a category buyers already understand; frame a value proposition that promises an outcome, not a feature; document points of parity so you don’t over-claim; highlight two to three competitive differentiation pillars; add proof; and cut jargon until a smart outsider gets it in one read.

Common failure modes include trying to be for everyone, leaning on feature soup instead of outcomes, skipping proof, and drifting from what the product can actually deliver. The fix is focus: fewer claims, clearer benefits, and evidence that eliminates buyer uncertainty.

If you need a fast start, run a 30-minute working session: five minutes to align on the target and problem, five to choose the category, ten to draft value proposition plus parity and differentiation, five to add proof, and five to define two experiments (one discovery conversation, one A/B test) that validate the language this week. Learn how other expert products do it and how to write one that sticks—then let data and customer language refine every word.

Great positioning earns clarity, confidence, and compounding advantage. When we get it right, the market tells us quickly—prospects move faster, users activate with less friction, and the team finally feels like it’s rowing in the same direction.

Inspired by this post on Product School.

November 13, 2025
Build a Company You’ll Run Forever: Bootstrapping vs VC, PMF, and the Art of ‘Eating Glass’

I’ve spent my career building products and teams that I intend to steward for the long haul, and I’m drawn to founders who treat company-building as a craft you can practice forever. In this analysis, I break down a journey that crystallizes what it takes: going from a teenage wholesale hustle to an API-first healthcare clearinghouse, and in the process, learning why execution isn’t a moat, why venture capital is “going pro,” and how “eating glass” can become a durable advantage.
Here’s the arc that anchored my thinking: a founder who, at 16, turned $2,500 into a wholesale empire; later bootstrapped a wildly profitable auto-parts business; then sold it to tackle “the most complicated problem” he’d ever encountered: business-to-business transaction exchange. He spent years building EDI infrastructure, threw away the entire codebase eight times, and found extraordinary traction in healthcare. The company recently raised a $70M Series B co-led by Stripe and Addition. The throughline is a consistent, high-agency approach to product management and go-to-market strategy, guided by first principles decision making.
The first customer is often the trickiest—not because demand doesn’t exist, but because the product’s value proposition, points of parity, and competitive differentiation are still coalescing. I push teams to do founder-led GTM early, speak in the user’s language, and orchestrate high-signal conversations that expose real switching costs. That’s how we avoid mistaking polite interest for product-market fit.
Bootstrapping forces rigor, but it also means being “constrained by capital.” There’s a ceiling to the speed at which you can iterate, validate, and scale. Venture capital, in the right context, is like “going pro”: you trade a bit of optionality for time, talent density, and a faster feedback loop. I often see confusion between ownership vs. control; structurally, you can design for alignment while still moving with the urgency a competitive market demands.
One theme I return to with my own teams: execution is never actually a moat. Processes can be copied. Culture can be mimicked superficially. What can’t be easily replicated is the willingness to do the unglamorous, compounding work—what the founder here called “eating glass.” It’s the daily discipline of simplifying the system, instrumenting the edge cases, and standing up operational excellence that compounds into true competitive differentiation.
When product-market fit hits in enterprise infrastructure, it can feel like “the snake swallowing a deer.” Capacity, process, and architecture are stretched to their limits all at once. I’ve experienced the same pattern: everything slows down so the organization can re-architect for scale. The trick is to make those constraints visible—measure service levels, queuing, and error budgets like you would in a production system—so you’re not flying blind.
Some of the strongest product-management instincts I’ve seen borrow from discount retail and Toyota. From discount retail, we learn to obsess over unit economics, operational throughput, and ruthless simplification. From the Toyota production system, we adopt Kanban / TPS (Toyota), continuous improvement, and respect for constraints. In software terms, this becomes fast deployment frequency, small batch sizes, and defect prevention at the source—because “All software is a cascade of miracles.”
Scaling decision-making is where most teams stall. I favor clear ownership, lightweight written narratives, and a bias for first principles decision making over committee compromise. That structure lets high-agency individuals move quickly while keeping cross-functional stakeholders aligned on outcomes vs output OKRs. It’s how you build empowered product teams without sacrificing focus.
Hiring is where philosophy becomes practice. I resonate with the onboarding mantra “everything’s your fault now”—not as blame, but as an invitation to own outcomes end to end. I look for high-agency people who demonstrate systems thinking and the capacity to simplify. Manager hiring should lag role clarity; bring in managers when coordination overhead is the limiting factor, not when it merely feels uncomfortable.
Longevity comes from founder-approach fit as much as product-market fit. Build a company you don’t want to leave by aligning operating cadence, decision rights, and cultural norms with how you actually work best. Maintain conviction in unconventional practice when the evidence supports it, while remembering that “Reality has a surprising amount of detail.” The more I zoom in on the real work—interfaces, edge cases, workflows—the more the right design emerges.
In healthcare EDI, that realism matters. HIPAA overview (HHS) sets the compliance baseline. Payer integrations with Aetna, Blue Cross Blue Shield, and Cigna demand reliability and deep domain fidelity. Cloud and back-office ecosystems—from AWS and NetSuite to Slack, Microsoft Teams, Zapier, and Clay—shape the surrounding workflow. Lessons from Amazon, Target, Walmart, and Costco inform operational rigor; supply chain analogies from Ford Motor Company and GM clarify interface contracts. Porter’s five forces helps frame market structure; perspectives from Jeff Bezos and Peter Thiel sharpen strategic posture.
If you’re building for the long run, here’s the blueprint I use with product leaders: validate painfully specific jobs-to-be-done before you scale; prefer founder-led GTM until messaging closes the intent-to-adoption gap; instrument throughput and quality like a production system; invest in people who treat ambiguity as a chance to lead; and don’t confuse speed with hurry. When the “snake swallowing a deer” moment arrives, re-architect deliberately, protect your margins, and let operational excellence carry you from product discovery to durable product-led growth.
References and resources: Aetna: https://www.aetna.com/, Amazon: https://www.amazon.com/, AWS: https://aws.amazon.com/, Blue Cross Blue Shield: https://www.bcbs.com/, Change Healthcare: https://www.changehealthcare.com/, Cigna: https://www.cigna.com/, Clay: https://www.clay.com/, Costco: https://www.costco.com/, Ford Motor Company: https://www.ford.com/, GM: https://www.gm.com/, HIPAA overview (HHS): https://www.hhs.gov/hipaa/index.html, Jeff Bezos: https://x.com/JeffBezos, Kanban / TPS (Toyota): https://global.toyota/en/company/vision-and-philosophy/production-system, Microsoft Teams: https://www.microsoft.com/microsoft-teams, NetSuite: https://www.netsuite.com/, O’Reilly Auto Parts: https://www.oreillyauto.com/, Peter Thiel: https://x.com/peterthiel, Porter’s five forces: https://www.isc.hbs.edu/strategy/pages/the-five-forces.aspx, “Reality has a surprising amount of detail”: https://johnsalvatier.org/blog/2017/reality-has-a-surprising-amount-of-detail, Slack: https://slack.com/, Stedi: https://www.stedi.com/, Summit Racing: https://www.summitracing.com/, Target: https://www.target.com/, Walmart: https://www.walmart.com/, Zapier: https://zapier.com/

November 6, 2025
My Product Positioning Playbook: Craft Unforgettable Messaging That Wins Markets and Endures

Every market-winning product I’ve helped build started with a positioning statement that was clear, defensible, and memorable. When I lead new initiatives at HighLevel, Inc., I treat positioning as a product decision—because it sets the guardrails for what we prioritize, how we execute, and how we tell the story across the entire go-to-market engine.

Your product positioning statement decides if you stand the test of time. Learn how other expert products do it and how to write one that sticks.

At its core, a positioning statement is the sharpest articulation of who we serve, the problem we solve, the category we compete in, the value proposition we deliver, and why we win. It is not a tagline or a pitch deck sentence; it’s the decision calculus that aligns product, marketing, sales, and customer success so we can move fast in one direction.

Here’s the simple template I use and coach teams on: For [target customer/segment] who [urgent need or job-to-be-done], [product name] is a [category or frame of reference] that [core value proposition]. Unlike [primary alternative or status quo], it [competitive differentiation and reasons to believe]. When this fits, everything from roadmaps to demos becomes easier—and conversions tend to follow.

Start with the target segment. Be precise about who you are for. I triangulate with retention analysis and behavioral data (e.g., Amplitude analytics) to find the cohorts that activate quickly, retain well, and expand. If you cannot name the segment in one line, you’ll struggle to land positioning anywhere else.

Next, define the customer outcome. Tie the promise to measurable “outcomes vs output OKRs.” Customers buy progress, not features. State the job-to-be-done in their language and anchor it to a business result they already track.

Choose your category and points of parity. Category is a cognitive shortcut; it tells buyers where you sit on their mental map. Points of parity are table stakes you must match to be considered. If you skip parity, you look incomplete; if you skip category, you look confusing.

Then sharpen your competitive differentiation and value proposition. What do you do uniquely well that competitors can’t easily copy? Back it up with reasons to believe—proof points like speed-to-value, measurable ROI, data governance, or privacy-by-design and cybersecurity commitments. Credibility turns claims into confidence.

Validate the statement through rigorous A/B testing. I pressure-test the language across landing pages, onboarding flows, in-app guides, sales call talk tracks, and nurture sequences. Tools like Pendo, Intercom, and HubSpot make it easy to instrument message experiments and see what actually moves activation, conversion, and expansion.

Operationalize the winning statement across go-to-market strategy and product-led growth motions. Bake it into onboarding, product tours, pricing pages, and demo narratives. A strong positioning statement should shape prioritization in the roadmap as much as it shapes the headline on your website.

Beware common pitfalls. Don’t confuse vibe marketing for positioning. Avoid vague superlatives that any competitor could claim. Don’t aim for universal appeal; specificity sells. And never let the statement drift—revisit it after major launches, new segments, or shifts in competitive dynamics.

Here’s an example using the template: For revenue teams at mid-market SaaS companies who need faster, more predictable pipeline creation, SignalFlow is a unified analytics platform that turns product usage signals into qualified opportunities. Unlike generic CRMs and static lead scoring, it surfaces intent in real time and automates outreach, improving conversion by 22% within 30 days.

If your team debates features more than outcomes, it’s time to revisit your positioning. In my experience, one crisp sentence can unlock alignment, accelerate execution, and make your message stick. Write it, test it, and make it the north star for every decision you ship.

Inspired by this post on Product School.

November 5, 2025
From Code to Roadmaps: My Proven Playbook for Engineers Becoming Product Managers

"From code commits to boardrooms. Here are real stories of software engineers who swapped bugs for roadmaps on the road to product manager." I’ve made that leap myself and helped many engineers do the same. In this piece, I share the playbook I use to guide high-potential ICs into impactful product management roles—without losing the engineering rigor that makes them special.

Engineers make exceptional product managers because we’re trained to decompose complex systems, debug ambiguity, and reason from first principles. The transition isn’t about abandoning code; it’s about expanding your scope from implementation details to customer outcomes, market context, and business impact.

The first shift is mental: move from shipping outputs to driving outcomes. Features are a means; value is the end. I anchor this change with outcomes vs output OKRs, ensuring every roadmap item ties to a measurable user or business result rather than a checklist of tickets.

Next, upskill deliberately in three areas: product discovery, product positioning, and stakeholder management. Learn to design unbiased customer interviews, synthesize patterns from qualitative and quantitative signals, and craft crisp value propositions that resonate with real segments. Then practice executive-ready communication—clear decisions, concise narratives, and no jargon crutches.

Here’s the practical, low-risk way to get PM experience without changing your title: form a product trios working group (design, engineering, product) around a real problem. Lead discovery with a weekly cadence, run lightweight experiments, and translate insights into a draft product roadmapping and sprint planning artifact. Ship small, learn fast, and narrate the learning.

Build a simple portfolio that proves product judgment. Include one-page problem briefs, discovery notes, customer quotes, prioritized opportunity trees, and a before/after roadmap snapshot. For each artifact, quantify the impact: activation lift, support ticket reduction, conversion improvement—whatever outcome your work influenced.

If you want to pivot internally, propose a 90-day experiment. Volunteer to own a well-bounded problem, commit to an outcomes dashboard, and set a weekly stakeholder update. Keep a minimal engineering contribution during the trial to de-risk the transition for your team while you demonstrate PM leverage across the squad.

If you’re interviewing externally, prepare two deep case studies: one discovery-led (how you reduced uncertainty) and one delivery-led (how you aligned stakeholders and shipped). Be explicit about trade-offs, risks you retired, metrics you moved, and lessons learned. The best signals of product sense are clarity under constraints and an ability to say “no” for good reasons.

Once you land the role, use a 30-60-90 plan. In the first 30 days, map users, workflows, metrics, and decision rhythms; in 60, run a focused discovery sprint and align on your hypothesis-led roadmap; by 90, deliver a thin slice that proves value and establishes credibility with empowered product teams. Keep your communication tight, your dashboards honest, and your customers close.

Common pitfalls: translating directly from solution space to roadmap without validating problems; equating stakeholder satisfaction with customer value; and mistaking velocity for progress. Avoid them by running small tests early, revisiting segment-specific value propositions, and anchoring trade-offs to product-market fit lessons.

If you’re standing at the edge of this transition, start where you are: choose one user pain, one measurable outcome, and one small bet. Treat it like a product: define success, experiment thoughtfully, and learn in public. The road from engineer to product manager isn’t a title change—it’s a shift in how you create value.

Inspired by this post on Product School.

November 3, 2025
10 Customer Acquisition Metrics I Obsess Over to Predict Growth (and Kill Vanity KPIs)

Stop chasing the wrong numbers! Learn which customer acquisition metrics actually point the way to growth and which to leave behind.

In my role leading product and growth, I’ve learned that sustainable acquisition comes from a disciplined focus on a few decisive signals. I run a tight scorecard that blends product-led growth inputs with sales-assisted outputs, stitched together in a unified analytics platform and grounded in our CRM integration. Tools like Amplitude analytics, HubSpot, Pendo, and Intercom help me see the entire journey—from first touch to user activation and revenue—without getting lost in dashboard noise.

ICP-qualified lead rate (MQL-to-SQL conversion) is my first gate. If qualified interest isn’t turning into sales conversations, I know our targeting, messaging, or handoff is off. This metric forces alignment between marketing and sales on the actual Ideal Customer Profile and disqualifies the “traffic for traffic’s sake” mindset.

Lead Velocity Rate (LVR) tells me whether next quarter’s growth is compounding. I track the month-over-month growth of qualified leads and opportunities, not raw leads. When LVR dips, I revisit go-to-market strategy and pipeline sources before the lagging revenue number shows trouble.

Activation rate is the heartbeat of product-led growth. I define a clear “first value” action and measure what percentage of new signups reach it within a set time window. Strong activation signals that our onboarding and value proposition are resonating; weak activation pushes me to refine in-app guides, product tours, and tooltip design.

Time-to-Value (TTV) measures how quickly new users experience the core benefit. Shorter TTV correlates with higher conversion, better retention, and lower support costs. I routinely A/B test onboarding steps, copy, and default settings to shave minutes off TTV without sacrificing comprehension.

Customer Acquisition Cost (CAC) by channel keeps us honest. I break out CAC for paid, organic, partner, and sales-led motions, then double-click into cohort performance. Channel-level CAC, tied back to revenue quality, helps me reallocate budget and resist the allure of cheap but low-intent clicks.

CAC payback period is my sanity check on efficiency. I want to know how many months of gross margin it takes to recover CAC—across each motion. When payback creeps up, we revisit pricing, packaging, onboarding friction, and top-of-funnel quality simultaneously.

LTV:CAC ratio shows whether we’re buying durable revenue. I pair it with retention analysis to avoid overestimating Lifetime Value. A healthy ratio without healthy retention is an illusion; I’d rather fix the product and activation leaks than pour more dollars into acquisition.

Win rate is the truth serum for positioning. If we’re losing qualified deals, I look for gaps in our points of parity, competitive differentiation, and proof points. Improving win rate often requires sharper product positioning and fewer—but stronger—value propositions.

Sales cycle length closes the loop between interest and impact. I segment cycle time by ICP, channel, and deal size to expose bottlenecks. Tightening cycle time compounds growth by accelerating cash and freeing capacity for more pipeline.

Organic acquisition share protects us from paid dependency. I aim for a rising share of signups from organic search, referrals, and product-led loops. Healthy organic signals resonance—a clear message-market fit that compounds over time.

To operate this system, I keep experiments rigorous. We set a minimum detectable effect (MDE) up front for key A/B tests so we don’t declare fake wins. Weekly cross-functional reviews keep us focused on outcomes vs output, and we only scale what demonstrably moves these ten metrics.

If you align your team around these signals and instrument the full journey end-to-end, you’ll make better bets faster. More importantly, you’ll stop celebrating vanity spikes and start compounding real, defensible growth.

Inspired by this post on Product School.

November 3, 2025
Go Hard Early: Enterprise AI Lessons That Built Serval’s Magical IT Automation Agents

Go hard early is more than a mantra—it’s a product strategy. When I study the most durable enterprise companies, I see the same pattern: you win by shipping fast, obsessing over the customer’s day-to-day pains, and delivering consumer-quality experiences to business buyers. That lens is exactly why Serval’s recent momentum caught my attention and why the lessons behind it matter for every product and IT leader building in AI.

Jake is the founder and CEO of Serval, an AI-driven IT automation and service management platform that just raised $47M in Series A funding this week. Before founding Serval, Jake spent over five years at Verkada, where he led multiple products from 0-1 and helped scale the company across hardware and software. His years at Verkada taught him that winning in enterprise means delivering consumer-quality experiences to business buyers — a lesson that shapes how Serval turns complex IT automation into something that feels magical.

From my vantage point, the most counterintuitive lesson here is the power of building “in existing categories.” Rather than inventing a new market, the better move can be to redefine expectations inside a known one—where buyers, budgets, and success criteria already exist. That’s how you compress sales cycles, build trust rapidly, and create a wedge for product-led growth without boiling the ocean.

Another playbook thread I admire: turning “hard mode” into a moat. The teams that lean into gnarly integrations, real workflow depth, and enterprise-grade reliability end up compounding an advantage that’s very hard for fast followers to copy. That mindset shows up in Serval’s platform strategy and, more importantly, in how they translate complex IT work into something that feels intuitive on day one and powerful on day 100.

Customer intimacy sits at the center of that strategy. The customer interview question that unlocked the IT buyer’s hidden pain points is the kind of move I try to operationalize across product trios and forward-deployed teams. When you ask not just, “What do you do?” but, “What do you do when everything breaks?” you surface the real constraints: shadow runbooks, brittle scripts, brittle processes, and the political friction that slows down response times. That’s where durable value—and competitive differentiation—lives.

How Serval’s automation builder uses AI to generate code-based workflows is a particularly smart architectural choice. Code-first doesn’t mean hard-to-use; it means source-controlled, interoperable, and shareable across teams—exactly what IT leaders want when automation moves from side project to system of record. Tie that to agentic orchestration and you get reliable automations with clear observability, safety rails, and the ability to scale without collapsing under edge cases.

I’m also a believer in redefining engineering and PM roles with forward-deployed engineers. When engineers partner directly with customers, discovery accelerates, prioritization sharpens, and product bet quality improves. You avoid ping-ponging requirements through layers, and you raise the hiring bar for true product creators who can think in outcomes, not just output.

Keeping the hiring bar high in an AI-native startup isn’t optional—it’s existential. The best teams screen for candidates who can reason from first principles, ship quickly with taste, and articulate the value proposition in plain language. The ultimate hiring litmus test is whether someone can improve the product on day one by clarifying a user journey, simplifying a workflow, or tightening a metric that actually matters.

There’s also Why there’s a “land grab” moment right now in enterprise AI. Incumbents are strong on breadth but often slow to re-architect for AI-native workflows. New entrants that show up with opinionated defaults, pragmatic security, and crisp buyer narratives can establish points of parity quickly while extending into true points of differentiation. That’s the window to seize—especially when building for mid-market and enterprise.

Here are the core themes I took away and how I translate them into practice across product roadmapping and sprint planning, product discovery, and go-to-market strategy.

Why building “in existing categories” can be more powerful than creating new ones. Use the market’s mental models, measure against known alternatives, and win by delivering a meaningfully better experience—not by forcing buyers to invent new procurement paths.

The lessons from Verkada that shaped Serval’s platform strategy. Treat UX polish as a strategic asset, make setup effortless, and let power users go deep without friction. Consumer-grade quality is not a veneer; it’s a trust accelerator in enterprise.

The customer interview question that unlocked the IT buyer’s hidden pain points. Go beyond happy-path discovery. Ask about the 3 a.m. moments, the panic buttons, and the messy handoffs—then design for those first.

How Serval’s automation builder uses AI to generate code-based workflows. Pair AI generation with reviewability, versioning, and safe rollbacks. Make it easy to see, test, and share what the agent is doing under the hood.

Redefining engineering and PM roles with forward-deployed engineers. Collapse feedback loops by putting builders where the problems are. It’s the fastest path to product-market fit lessons and real-world reliability.

Keeping the hiring bar high in an AI-native startup. Look for taste, speed, and ownership. Optimize for people who can both prototype with gen ai and ship production-hardened systems.

Why there’s a “land grab” moment right now in enterprise AI. Move quickly, but anchor on outcomes. Land with a wedge use case, expand with measurable value, and maintain clear points of parity while you deepen differentiation.

If you want to follow or explore the companies and leaders referenced, these links are a useful starting point.

LinkedIn: https://www.linkedin.com/in/jakestauch/

Twitter/X: https://x.com/jakeserval

LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/

Twitter/X: https://twitter.com/brettberson

Website: https://firstround.com/

First Round Review: https://review.firstround.com/

Twitter/X: https://twitter.com/firstround

YouTube: https://www.youtube.com/@FirstRoundCapital

This podcast on all platforms: https://review.firstround.com/podcast

References:

Alex McLeod: https://www.linkedin.com/in/alexmcleodio/

Clay: https://www.clay.com

Cloudflare: https://www.cloudflare.com

Cursor: https://cursor.sh

Filip Kaliszan: https://www.linkedin.com/in/kaliszan/

Hans Robertson: https://www.linkedin.com/in/hansrobertson

Linear: https://linear.app

Okta: https://www.okta.com

Rippling: https://www.rippling.com

Serval: https://www.serval.com/

ServiceNow: https://www.servicenow.com

Verkada: https://www.verkada.com

Workday: https://www.workday.com

Timestamps and topic highlights for easy navigation and deeper study:

(02:25) Lessons from holding different product roles

(07:29) Turning “hard mode” into a moat

(10:49) The early days of Serval

(12:59) Scratching the founder itch

(14:57) Unconventional interview techniques

(17:47) Solving core interview challenges

(21:10) Planning the early product roadmap

(23:03) The surprising power of patience

(26:12) Serval’s impressive technical advantage

(27:35) Disrupting legacy incumbents

(31:13) Building for mid-market and enterprise

(33:35) Serval’s enduring roadmap

(36:08) How to sell to an existing market

(39:16) The evolving role software plays

(43:55) Building for AI that didn’t exist yet

(49:49) Serval’s forward-deployed engineers

(58:31) The hybrid PM-GM

(1:00:27) “You can over-prioritize”

(1:02:48) The unexpected value of panic buttons

(1:04:50) What Serval looks for in new talent

(1:07:01) The ultimate hiring litmus test

(1:13:59) Building out Serval’s go-to-market function

(1:16:31) The evolving IT market in 2025

My bottom line: build where budgets already live, ship with uncompromising UX, embed engineers with customers, and hold the line on talent. Do that, and you won’t just keep up with the enterprise AI “land grab”—you’ll define the standard others have to meet.

October 25, 2025
Why Retention Wins: The Ultimate Product Strategy to Shape Your Roadmap and Ignite Growth

I keep coming back to one simple truth in product management: Retention Is the Ultimate Product Strategy. When customers stay and expand, it signals that we are repeatedly solving real problems with a value proposition strong enough to withstand time, alternatives, and change.

Retention reveals if your product delivers lasting value. Learn how top product leaders use it to guide strategy, shape roadmaps, and drive growth.

At HighLevel, I treat retention as the clearest signal of product-market fit quality and the most reliable compass for product-led growth. I review retention weekly, cohort it by segment and plan, and tie it directly to value moments in onboarding and activation. If we can’t see where users succeed (or stall), we can’t shape a roadmap that consistently compounds value.

Here is how I put retention at the center of product strategy. When cohorts are strong, I double down on the experiences and workflows that create habit loops and advocacy. When cohorts drop, I stop chasing surface-level outputs and run focused product discovery to clarify the value proposition, reduce time-to-first-value, and reset outcomes vs output OKRs so teams are solving for the right problems.

I then translate retention insights into product roadmapping and sprint planning. Every roadmap theme must map to a retention driver: faster activation, deeper engagement, or expanded breadth of use. I use A/B testing to validate critical UX decisions, and I guard against false positives by aligning experiments to business outcomes tied to retention, not just clicks or vanity metrics.

Instrumentation matters. I rely on Amplitude analytics to trace the path from first touch to recurring value, measuring drop-offs, leading indicators of habit formation, and usage cliffs by persona. With clean event data, I can connect improvements in onboarding to cohort lift and quantify what features actually move long-term retention, not just short-term engagement.

Most retention gains come from the “boring but pivotal” basics: a frictionless onboarding flow, clear in-product guidance, and a crisp path to the first “aha” moment. I continually refine these with targeted improvements, then reinforce them with contextual education and lifecycle touchpoints that help customers unlock the next milestone of value.

I also segment retention to find hidden opportunities. Different plans, industries, and team sizes have distinct activation thresholds and success criteria. By tailoring experiences and success metrics per segment, we avoid one-size-fits-all decisions and build for real-world diversity while still maintaining a coherent roadmap.

Culturally, retention is how I keep product management leadership grounded. It forces ruthless prioritization, sharpens stakeholder conversations, and aligns teams on outcomes. When teams see their work reflected in month-over-month cohort lift, motivation rises—and so does our confidence in the strategy.

If you’re looking to operationalize this approach, start with a baseline retention analysis, define your key value moments, align a handful of outcomes vs output OKRs to activation and engagement, instrument the journey in Amplitude analytics, and prioritize one or two onboarding improvements that shorten time-to-first-value. Ship, measure, and iterate. Over time, this creates a roadmap that writes itself from the evidence of durable customer value.

Inspired by this post on Amplitude – Best Practices.

October 24, 2025
Build a Fearless Culture of Experimentation: How I Turn Tests into Teamwide Habits

I’ve learned the hard way that experiments stall when they’re treated like items to check off a backlog. Real impact shows up when experimentation becomes the way we think, plan, and decide—every day, across the entire product organization.

Successful experimentation isn't just about adopting new tools or running more tests. It’s about changing company culture.

At HighLevel, I anchor experimentation in outcomes, not output. We form product trios and empower product teams to own the problem, link work to outcomes vs output OKRs, and commit to fast learning loops. This isn’t about more activity; it’s about better decisions, tighter focus, and measurable customer value.

Our teams write crisp hypotheses, define decision rules up front, and set a minimum detectable effect (MDE) before any A/B testing begins. That small discipline prevents “result fishing,” speeds up decisions, and aligns everyone on what will constitute a real signal versus noise.

Tooling helps, but only when it serves the culture. We instrument experiences end-to-end, lean on Amplitude analytics within a unified analytics platform, and run retention analysis alongside acquisition metrics so we don’t celebrate shallow wins. The goal isn’t dashboards; it’s actionable insight that improves product-market fit lessons and informs the next iteration.

Rituals make the culture durable. We review experiments weekly, tie learnings back to OKRs during QBRs, and celebrate invalidated hypotheses as progress. That psychological safety turns “being wrong” into momentum, reinforcing product management leadership behaviors we want to scale.

We also invest in decision hygiene: clear problem statements, pre-registered success criteria, and simple templates that make it easy to do the right thing quickly. Over time, this reduces debate theater and increases the surface area for discovery—more time with customers, more signals, and more conviction in our bets.

If you’re starting from scratch, begin small: pick one critical journey, articulate a hypothesis, choose a primary metric and MDE, run a lean A/B test, decide ahead of time how you’ll act on outcomes, and close the loop publicly. Repeat that cadence until it becomes muscle memory. That’s how experiments stop being one-off projects and start compounding into product-led growth.

When experimentation is a culture, not a task, teams move faster, leaders make clearer tradeoffs, and customers feel the difference. That is the habit I continue to build—one hypothesis, one decision rule, and one learning loop at a time.

Inspired by this post on Amplitude – Perspectives.

October 24, 2025
Master Points of Parity in SaaS: Nail Table Stakes, Earn Trust, and Unlock Differentiation

Early in any market, I obsess over one thing before splashy features or clever messaging: are we meeting the table stakes that buyers expect? Points of parity (POPs) are the baseline capabilities that put us on a buyer’s shortlist and establish the credibility to compete. Without them, even the best differentiators won’t land.

Understand how points of parity are crucial to getting your foot in the door. Explore different strategies to make POPs work for your SaaS business.

Here’s how I define POPs in practice: they’re the “no-regrets” features, assurances, and experiences that customers assume you have because your competitors already do. In SaaS, that often includes security certifications (e.g., SOC 2), SSO, predictable performance (SLAs/Uptime), clear pricing, responsive support, and integrations with the rest of the customer’s stack.

POPs differ from points of difference (PODs). PODs are what make you unique; POPs are what make you viable. I’ve seen teams try to lead with innovation before building credibility, only to stall in procurement. You earn the right to showcase differentiation after you meet parity.

For SaaS, POPs frequently map to procurement checklists. Think InfoSec reviews, role-based access controls, audit logs, encryption standards, user management, and integrations with systems like Salesforce, HubSpot, or Slack. These aren’t glamorous, but they remove friction, reduce perceived risk, and accelerate time-to-value—cornerstones of product-led growth and a healthy go-to-market motion.

To identify the right POPs, I triangulate across four inputs: customer interviews focused on buying criteria, win/loss analysis to understand disqualifiers, competitor teardowns to benchmark table stakes, and support data to spot recurring gaps eroding trust. Collectively, these inputs reveal the minimum viable promises we must keep.

Prioritization matters. I translate POPs into outcomes (not output) and align them with our roadmapping and sprint planning. For example, instead of “Ship SSO,” I set an objective like “Reduce enterprise security objections by 60%” and measure RFP pass rates, security review cycle time, and sales stage conversion. This keeps us anchored to impact, not just checkboxes.

Execution should be pragmatic. With POPs, “good enough” is often the right bar—reliable, discoverable, and well-documented. Over-engineering POPs slows you down and diverts resources from differentiation. I focus on stable defaults, clear UX patterns, great docs, and in-app guides that help users activate parity features without friction.

Measuring POP health is straightforward if you wire it into your system. I monitor activation rates for parity features (e.g., SSO enabled), support volume tied to trust blockers (security, performance, billing), and the presence of POP gaps in win/loss notes. Retention and expansion are the ultimate validators: when POPs are solid, renewal conversations shift from risk mitigation to value creation.

Consider two tangible examples. For a messaging platform, POPs may include 99.9% uptime, message deliverability guarantees, two-factor authentication, and role-based permissions. For a product analytics tool, POPs could include granular event tracking, user privacy controls, standard dashboards, and self-serve onboarding. None differentiate you alone, but missing any one of them can disqualify you.

Common pitfalls I warn teams about: over-indexing on shiny features while losing deals on basics; inconsistent messaging that promises parity you can’t operationalize; ignoring pricing and packaging parity (buyers expect clear tiers and predictable billing); and underinvesting in enablement, leaving sales to “sell around” missing POPs.

Communicating POPs is as important as building them. I make sure parity shows up on our pricing page, security and reliability pages, and in crisp one-pagers for buying committees. In the product, I highlight parity features during onboarding with checklists and tooltips so customers experience trust quickly. For founder-led GTM, a tight narrative—“Yes, we meet the table stakes; here’s where we go beyond”—keeps discovery calls focused on outcomes.

My playbook is simple: meet parity fast, prove reliability visibly, and then pour fuel on your differentiators. When POPs are nailed, sales cycles shorten, support debt drops, and your unique value finally gets the stage time it deserves.

Inspired by this post on Amplitude – Best Practices.

October 23, 2025
The 7% Retention Rule: Why Week-One Return Rates Predict Long-Term Product Growth

I’ve learned that the fastest way to forecast a product’s trajectory is to zoom in on what happens in the first seven days. If we can get new users to return in week one, everything else gets easier—onboarding, expansion, advocacy. If we can’t, no amount of roadmap heroics will save us. That’s why I anchor early product reviews and growth plans around a simple but powerful heuristic: the 7% retention rule.

Discover why 7% of users returning after one week signals long-term growth, and how early activation separates top-performing products from the rest.

Here’s how I interpret the rule in practice. When a new cohort hits “activation” within their first session and at least 7% come back the following week, the retention curve usually flattens at a healthy level. That week-one return rate is a leading indicator of product-market fit, not a vanity metric. It tells me we’ve delivered time-to-value quickly, created a habit-forming loop, and built a reason to return that isn’t dependent on paid reminders or one-off promotions.

The operative word is activation. Teams that define activation rigorously win more often. I start by clarifying the critical action that correlates with ongoing value (for example: completing a key setup, sending the first campaign, integrating data, or inviting collaborators). Then I instrument the journey to that moment. Amplitude analytics or a unified analytics platform makes this straightforward: cohort analysis for new users, funnels for step-drop, and event-level insights to isolate friction.

To lift week-one returns, I focus on three levers: time-to-value, habit loops, and lifecycle nudges. On time-to-value, we remove steps, pre-fill defaults, and build progressive setup so value appears before configuration fatigue sets in. For habit loops, we connect the activation to a recurring trigger (alerts, scheduled tasks, shared artifacts) and ensure the outcome is visible and motivating. For lifecycle nudges, we use contextual messaging—not blast emails—to pull users back to the next best action.

Operationally, I treat the 7% threshold as a guardrail in our outcomes vs output OKRs. Product trios own the activation metric, with a weekly ritual: review the new-user cohort, segment by acquisition channel and persona, and run a tight experiment cadence (copy, UX, pricing hints, or education). We prioritize by expected retention lift, not by effort alone. When the metric is below 7%, all-hands focus shifts to activation; once it’s consistently above 7%, we compound gains through expansions, collaboration features, and monetization experiments.

A final note on leadership and teams: empowered product teams move the activation needle faster because they can ship instrumentation, messaging, and UX tweaks without cross-functional gridlock. Clear ownership, a crisp activation definition, and shared visibility make the difference between incremental progress and compounding growth.

If you’re evaluating a new product today, start with the week-one story. Verify activation, measure return rate, and check whether the curve flattens. If the line is under 7%, you don’t have a growth problem—you have an activation problem. Fix that first, and long-term retention and revenue will follow.

Inspired by this post on Amplitude – Best Practices.

October 23, 2025
Stop the Leaky Bucket: Proven Playbook to Turn User Acquisition into Lasting Growth

I've led products through dazzling acquisition spikes only to watch churn quietly erase the gains. More users don't automatically mean more long-term growth. In our world, that disconnect is the leaky bucket problem: every new signup pours water into a bucket riddled with holes across activation, engagement, monetization, and advocacy.

Losing users as fast as you acquire them? Get exclusive insights from our 2025 Product Benchmark Report on how to fix the leaky bucket problem and drive lasting growth.

When I diagnose this problem, I start by shifting the conversation from top-of-funnel volume to full-lifecycle health. I look at cohort retention curves, time-to-value, activation rates, depth and frequency of core actions, and expansion revenue. These metrics reveal whether we have true product-market fit, whether our onboarding accelerates value discovery, and where users fall out before they experience a durable “aha.”

My playbook is rigorous and repeatable. I instrument a unified analytics platform to produce clean, decision-grade metrics. I define a single, canonical activation moment that ties to value, and segment it by ideal customer profiles to avoid averages hiding the truth. I run product trios to close the gap between discovery and delivery. I set outcomes vs output OKRs so the team aligns on retention and engagement, not just shipping features. And I connect roadmap bets to measurable behaviors that lead indicators predict—never vanity metrics.

Onboarding is where I usually find the biggest, fastest wins. I trim steps, reduce cognitive load, and default users into best-practice templates so they achieve value in minutes, not weeks. I use contextual education, empty states that teach by doing, and lifecycle messaging triggered by real behavior. Then I close the loop with customer success by aligning QBRs vs OKRs so feedback from high-value accounts translates into clear product outcomes, not feature requests.

Pricing and packaging matter more than most teams realize. If SaaS pricing doesn’t map to realized value, expansion stalls and churn rises. I align paywalls to natural milestones in the journey (usage thresholds tied to success), avoid early friction on critical adoption paths, and make upgrades an obvious outcome of growing value rather than a forced gate.

Execution discipline turns strategy into lift. I run weekly growth reviews that pair qualitative discovery with quantitative signal, keep an experiment backlog prioritized by expected impact and confidence, and insist on clean experiment design (counterfactuals, guardrails, and holdouts). Typical high-leverage tests include reducing time-to-first-value, clarifying the core job-to-be-done in the first session, and collapsing setup with smart defaults and in-product guidance.

The pattern is consistent: when we measure what matters, build with empowered product teams, and commit to outcome-driven roadmaps, the bucket stops leaking. Acquisition starts compounding because each cohort retains better than the last. If your growth feels like running on a treadmill, it’s time to refocus on activation, engagement, and retention—and use benchmarks to calibrate where you are versus where durable growth lives.

Inspired by this post on Amplitude – Best Practices.

October 23, 2025